Geostatistical Analysis of County-Level Lung Cancer Mortality Rates in the Southeastern United States.
Geostatistical Analysis of County-Level Lung Cancer Mortality Rates in the Southeastern United States.
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DOI：
10.1111/j.1538-4632.2009.00781.x
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发表时间：
2010-01-01
影响因子：
3.6
通讯作者：
Goovaerts P
中科院分区：
文献类型：
--
作者：
Goovaerts P
分析健康数据和假设的协变量，如环境、社会经济、人口、行为或职业因素，是地质统计学的一个很有前途的应用。然而，将最初为分析地球特性而开发的方法转移到健康科学中，带来了几个方法和技术挑战。这是因为健康数据通常是在不规则的空间支持(例如县)上聚合的，并且由分子和分母(即比率)组成。本文概述了专为区域健康数据特征量身定做的地统计学方法，并将其应用于美国东南部688个县(1970-1994)的肺癌死亡率。阶乘泊松克里格法可以过滤短期变化和噪声，这在人口稀少的县可能是很大的，以揭示男性和女性癌症死亡率的相似区域模式，这些模式与造船厂的邻近程度很好地相关。比率不确定性通过使用随机模拟的局部聚类分析来传递，从而允许计算癌症死亡率低或高的集群的可能性。考虑到人口规模和比率的不确定性，导致在橡树岭国家实验室周围发现了新的高死亡率集群，男性在养猪场和造纸业高度集中的县(职业暴露)，女性在亚特兰大附近。
The analysis of health data and putative covariates, such as environmental, socioeconomic, demographic, behavioral, or occupational factors, is a promising application for geostatistics. Transferring methods originally developed for the analysis of earth properties to health science, however, presents several methodological and technical challenges. These arise because health data are typically aggregated over irregular spatial supports (e.g., counties) and consist of a numerator and a denominator (i.e., rates). This article provides an overview of geostatistical methods tailored specifically to the characteristics of areal health data, with an application to lung cancer mortality rates in 688 U.S. counties of the southeast (1970–1994). Factorial Poisson kriging can filter short-scale variation and noise, which can be large in sparsely populated counties, to reveal similar regional patterns for male and female cancer mortality that correlate well with proximity to shipyards. Rate uncertainty was transferred through local cluster analysis using stochastic simulation, allowing the computation of the likelihood of clusters of low or high cancer mortality. Accounting for population size and rate uncertainty led to the detection of new clusters of high mortality around Oak Ridge National Laboratory for both sexes, in counties with high concentrations of pig farms and paper mill industries for males (occupational exposure) and in the vicinity of Atlanta for females.
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影响因子：
2.6
作者：
Goovaerts, P.
通讯作者：
Goovaerts, P.
DOI：
10.1198/016214502388618438
发表时间：
2002-09-01
影响因子：
3.7
作者：
Kelsall, J;Wakefield, J
通讯作者：
Wakefield, J
影响因子：
3.1
作者：
Monestiez, P;Dubroca, L;Guinet, C
通讯作者：
Guinet, C
影响因子：
2.9
作者：
Greiling, Dunrie A;Jacquez, Geoffrey M;Rommel, Robert G
通讯作者：
Rommel, Robert G
影响因子：
3.6
作者：
ANSELIN, L
通讯作者：
ANSELIN, L